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- Extract, transform, load - Wikipedia
Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container The data can be collected from one or more sources and it can also be output to one or more destinations
- What is ETL (extract, transform, load)? - IBM
What is ETL? ETL—meaning extract, transform, load—is a data integration process that combines, cleans and organizes data from multiple sources into a single, consistent data set for storage in a data warehouse, data lake or other target system
- What is ETL? - Extract Transform Load Explained - AWS
Extract, transform, and load (ETL) is the process of combining data from multiple sources into a large, central repository called a data warehouse ETL uses a set of business rules to clean and organize raw data and prepare it for storage, data analytics, and machine learning (ML)
- ETL Process in Data Warehouse - GeeksforGeeks
In short, the ETL process involves extracting raw data from various sources, transforming it into a clean format and loading it into a target system for analysis
- Extract, transform, load (ETL) - Azure Architecture Center
Extract, transform, load (ETL) is a data integration process that consolidates data from diverse sources into a unified data store During the transformation phase, data is modified according to business rules using a specialized engine
- What is ETL (extract transform load)? - Informatica
ETL is a three-step data integration process used to synthesize raw data from a data source to a data warehouse, data lake, or relational database Data migrations and cloud data integrations are common use cases for ETL
- ETL Process Tools | SAS
ETL is a type of data integration that refers to the three steps (extract, transform, load) used to blend data from multiple sources It's often used to build a data warehouse
- What is ETL? - Google Cloud
ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data
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